code: def _eval(model, in_data):
      # run in eval mode
      model.eval()
      for _ in range(5):
          out = model(in_data)
      # adding torch.no_grad()
      for _ in range(5):
          with torch.no_grad():
              out = model(in_data)
  
file_path: fairscale/tests/nn/data_parallel/test_fsdp_shared_weights_mevo.py
imports: from copy import deepcopy
  import pytest
  import torch
  from torch import nn
  import torch.multiprocessing
  from torch.optim import SGD
  from fairscale.experimental.nn import MEVO
  from fairscale.fair_dev.testing.testing import dist_init, in_circle_ci, objects_are_equal, skip_if_single_gpu, teardown, temp_files_ctx
  from fairscale.nn.data_parallel import FullyShardedDataParallel
label_desc: Use image node_id 4 for calling a global function with example usage: _eval(model, in_data) without return types